Lessons Learned from Implementing Service-Oriented Clinical Decision Support at Four Sites: A Qualitative Study

Objective To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Methods Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. Results We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Discussion Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. Conclusion The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services

Report on the EHCR (Deliverable 26.1)

The challenge of richly interpreting electronic health information, in order to populate EHR instances with suitable terms, to provide decision support in the care of individuals, to identify suitable patients for teaching or clinical trials recruitment, and to mine populations of records for public health or to discover new medical knowledge, all require that the heterogeneous clinical entry instances within EHR repositories can be systematically analysed and interpreted. Achieving this requires the combination and co-operation of many different health informatics tools and technologies, underpinned by shared representations of clinical concepts and inferencing formalisms. Much of this work is at the level of R&D, and is well represented across the Semantic Mining consortium. The challenge of WP26 is to build up a vision of the ways in which these historically independent threads of health informatics research can collaborate, and uncover the research challenges that are needed in order to deliver good demonstrations of semantically indexed and richly analysable EHRs. The partners have begun WP26 by acquiring a better knowledge of each other’s areas of endeavour, and are beginning to steer their research interests towards future areas of collaboration

Using a Service Oriented Architecture Approach to Clinical Decision Support: Performance Results from Two CDS Consortium Demonstrations

The Clinical Decision Support Consortium has completed two demonstration trials involving a web service for the execution of clinical decision support (CDS) rules in one or more electronic health record (EHR) systems. The initial trial ran in a local EHR at Partners HealthCare. A second EHR site, associated with Wishard Memorial Hospital, Indianapolis, IN, was added in the second trial. Data were gathered during each 6 month period and analyzed to assess performance, reliability, and response time in the form of means and standard deviations for all technical components of the service, including assembling and preparation of input data. The mean service call time for each period was just over 2 seconds. In this paper we report on the findings and analysis to date while describing the areas for further analysis and optimization as we continue to expand our use of a Services Oriented Architecture approach for CDS across multiple institutions

Towards optimal use of antithrombotic therapy of people with cancer at the end of life: a research protocol for the development and implementation of the SERENITY shared decision support tool Thrombosis Research

Background: Even though antithrombotic therapy has probably little or even negative effects on the well-being of people with cancer during their last year of life, deprescribing antithrombotic therapy at the end of life is rare in practice. It is often continued until death, possibly resulting in excess bleeding, an increased disease burden and higher healthcare costs. Methods: The SERENITY consortium comprises researchers and clinicians from eight European countries with specialties in different clinical fields, epidemiology and psychology. SERENITY will use a comprehensive approach combining a realist review, flash mob research, epidemiological studies, and qualitative interviews. The results of these studies will be used in a Delphi process to reach a consensus on the optimal design of the shared decision support tool. Next, the shared decision support tool will be tested in a randomised controlled trial. A targeted implementation and dissemination plan will be developed to enable the use of the SERENITY tool across Europe, as well as its incorporation in clinical guidelines and policies. The entire project is funded by Horizon Europe.Results: SERENITY will develop an information-driven shared decision support tool that will facilitate treatment decisions regarding the appropriate use of antithrombotic therapy in people with cancer at the end of life. Conclusions: We aim to develop an intervention that guides the appropriate use of antithrombotic therapy, prevents bleeding complications, and saves healthcare costs. Hopefully, usage of the tool leads to enhanced empowerment and improved quality of life and treatment satisfaction of people with advanced cancer and their care givers

Redesigning Nursing Education: Lessons Learned from the Oregon Experience

Offers evaluation findings, lessons learned, and guidance from a coalition of community colleges and university nursing programs that offer a standard competency-based curriculum to enable students to make a seamless transition and raise skill levels

Towards optimal use of antithrombotic therapy of people with cancer at the end of life: A research protocol for the development and implementation of the SERENITY shared decision support tool

Anticoagulants; Hemorrhage; ThrombosisAnticoagulantes; Hemorragia; TrombosisAnticoagulants; Hemorràgia; TrombosiBackground Even though antithrombotic therapy has probably little or even negative effects on the well-being of people with cancer during their last year of life, deprescribing antithrombotic therapy at the end of life is rare in practice. It is often continued until death, possibly resulting in excess bleeding, an increased disease burden and higher healthcare costs. Methods The SERENITY consortium comprises researchers and clinicians from eight European countries with specialties in different clinical fields, epidemiology and psychology. SERENITY will use a comprehensive approach combining a realist review, flash mob research, epidemiological studies, and qualitative interviews. The results of these studies will be used in a Delphi process to reach a consensus on the optimal design of the shared decision support tool. Next, the shared decision support tool will be tested in a randomised controlled trial. A targeted implementation and dissemination plan will be developed to enable the use of the SERENITY tool across Europe, as well as its incorporation in clinical guidelines and policies. The entire project is funded by Horizon Europe. Results SERENITY will develop an information-driven shared decision support tool that will facilitate treatment decisions regarding the appropriate use of antithrombotic therapy in people with cancer at the end of life. Conclusions We aim to develop an intervention that guides the appropriate use of antithrombotic therapy, prevents bleeding complications, and saves healthcare costs. Hopefully, usage of the tool leads to enhanced empowerment and improved quality of life and treatment satisfaction of people with advanced cancer and their care givers

Membrane transporters in drug development

Membrane transporters can be major determinants of the pharmacokinetic, safety and efficacy profiles of drugs. This presents several key questions for drug development, including which transporters are clinically important in drug absorption and disposition, and which in vitro methods are suitable for studying drug interactions with these transporters. In addition, what criteria should trigger follow-up clinical studies, and which clinical studies should be conducted if needed. In this article, we provide the recommendations of the International Transporter Consortium on these issues, and present decision trees that are intended to help guide clinical studies on the currently recognized most important drug transporter interactions. The recommendations are generally intended to support clinical development and filing of a new drug application. Overall, it is advised that the timing of transporter investigations should be driven by efficacy, safety and clinical trial enrolment questions (for example, exclusion and inclusion criteria), as well as a need for further understanding of the absorption, distribution, metabolism and excretion properties of the drug molecule, and information required for drug labelling. © 2010 Macmillan Publishers Limited

Pharmacogenomic testing and its future in community pharmacy

Although it is common to see pharmacogenomic testing used North America and Australia, it is not yet part of practice in the UK. With the promise of genomic screening becoming part of the NHS, pharmacists must equip themselves with a knowledge of how the process works. Source: Shutterstock.com In January 2019, the UK government unveiled its ten-year plan for NHS England and emphasised the role pharmacists can play in promoting patient self-care[1]. There was also a focus on delivering value from medicines and reducing avoidable medicines related-harm, which costs the NHS a minimum of £98.5m per year[2]. This coincides with the NHS Genomic Medicine Service, which will be rolled out across England from April 2020, meaning that the routine use of genomic screening and personalised treatments will be the new normal in the NHS[3],[4]. Pharmacists’ advice currently relies on knowledge of observable patient characteristics, such as age, weight, comorbidities and concurrent medicines, while largely disregarding genetics. However, it is estimated that genetic factors could contribute to between 25–50% of inappropriate drug responses[5]. Knowing exactly which medicine to use for a patient and which to avoid can be a challenging task in clinical practice. However, pharmacogenomics can provide the prescriber with additional information on some of the unobserved patient characteristics that affect drug response — this can assist with both drug selection and safety. Therefore, the combination of this pharmacogenomic information along with other factors influencing pharmaceutical care may provide an opportunity to deliver more ‘personalised’ medicine, facilitating better selection and reducing the need for ‘trial and error’ prescribing